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Construction of a Wireless-Enabled Endoscopically Implantable Sensor for pH Monitoring with Zero-Bias Schottky Diode-based Receiver

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A low emission, low power non-linear frequency modulation based transmitter for implanted devices.

Ruchir Saraswat, Esther Rodriguez-Villegas

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|October 11, 2013

Summary

This study introduces a novel non-linear frequency modulator designed to reduce electromagnetic interference (EMI) for transmitting neural signals. The new design is crucial for developing low-emission embedded medical devices.

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Area of Science:

Biomedical Engineering
Signal Processing
Microelectronics

Background:

The increasing prevalence of embedded medical devices necessitates the development of components with low Electromagnetic Interference (EMI) and Radio Frequency Interference (RFI).
Existing frequency modulation techniques may not adequately address the stringent EMI/RFI requirements for neural signal transmission in sensitive medical applications.

Purpose of the Study:

To propose and evaluate a novel non-linear frequency modulator for neural signal transmission that minimizes EMI.
To offer an alternative to traditional phase-locked loop (PLL) based modulators for low-emission applications.

Main Methods:

A non-phase locked loop (non-PLL) based frequency modulator architecture was designed.
A ramp-based encoding scheme was employed to represent the neural amplifier's bit stream.
A non-linear modulation signal was utilized to modify the encoded signal, aiming to reduce the peak of the power spectrum.

Main Results:

The proposed non-linear frequency modulator effectively lowers the peak of the power spectrum, a key indicator of electromagnetic interference.
The algorithm was successfully implemented and tested using 0.18µ AMS technology.

Conclusions:

The developed non-linear frequency modulator presents a viable solution for low-emission neural signal transmission.
This approach contributes to the design of safer and more reliable embedded medical devices with reduced EMI/RFI.